Commit 7dacb6f1 authored by Alan O'Cais's avatar Alan O'Cais

Update readme.rst

parent 3f332871
......@@ -55,9 +55,9 @@ The electrostatic force calculation usually represents the main computational co
The Smooth Particle Mesh Ewald [SPME]_ splits the electrostatic forces in two parts: a short range, solved in the real space, and a long range, solved in the Fourier space.
An error weight function combines the two contributions. For the long range force the electrical charges are spread on a virtual particle mesh using a B-spline interpolation function.
Porting to GPU the full short and long range interactions allowed to maintain the speedup factor of x4 when compared to a traditional 12-core Intel CPU.
Porting the full short and long range interactions to GPUs allowed us to achieve a speedup factor of 4x when compared to a traditional 12-core Intel CPU.
One of the main applications which included electrical charges are the simulations of plasma.
One of the main applications which includes electrical charges are the simulations of plasma.
......@@ -66,10 +66,10 @@ _________________
.. Keep the helper text below around in your module by just adding ".. " in front of it, which turns it into a comment
The Ewald summation method above described scales with :math:`N^{1.5}` at best, where N is the number of charged particles. The SPME allows a better scaling, :math:`N*log(N)`,
but requires a stencil domain decomposition (i.e. decomposing the domain along one direction only) to allow the FFTW library scaling with more than 1 core.
If this is not used, as in the current master version of DL\_MESO\_DPD, the FFTW becomes rapidly a bottleneck for scaling across several nodes.
On the other side, the porting to a single GPU does not need domain decomposition and the same speedup factor (x4 compared to 12-core Intel) is mainteined.
The Ewald summation method scales with :math:`N^{1.5}` at best, where N is the number of charged particles. The SPME method allows for improved scaling, :math:`N*log(N)`,
but requires a stencil domain decomposition (i.e. decomposing the domain along one direction only) to allow the FFTW library to scale with more than 1 core.
If this is not used, as in the current master version of DL\_MESO\_DPD, FFTW rapidly becomes a bottleneck for scaling across several nodes.
On the other hand, the porting to a single GPU does not need domain decomposition and the same speedup factor (4x compared to 12-core Intel) is maintained.
......@@ -79,12 +79,12 @@ ______________________
.. Keep the helper text below around in your module by just adding ".. " in front of it, which turns it into a comment
This module is part of the DL_MESO_DPD code. Full support and documentation is available at:
This module is part of the DL\_MESO\_DPD code. Full support and documentation is available at:
* https://www.scd.stfc.ac.uk/Pages/DL_MESO.aspx
* https://www.scd.stfc.ac.uk/Pages/USRMAN.pdf
To download the DL_MESO_DPD code you need to register at https://gitlab.stfc.ac.uk/dl_meso/dl_meso.
To download the DL\_MESO\_DPD code you need to register at https://gitlab.stfc.ac.uk/dl_meso/dl_meso.
Please contact Dr. Micheal Seaton at Daresbury Laboratory (STFC) for further details.
......@@ -95,7 +95,7 @@ ____________________
.. Keep the helper text below around in your module by just adding ".. " in front of it, which turns it into a comment
The DL_MESO code is developed using git version control. Currently the GPU version is under a branch named "add_gpu_version". After downloading the code, checkout the GPU branch and look into the "DPD/gpu_version" folder, i.e:
The DL\_MESO code is developed using git version control. Currently the GPU version is under a branch named "add\_gpu\_version". After downloading the code, checkout the GPU branch and look into the "DPD/gpu\_version" folder, i.e:
* git clone DL_MESO_repository_path
* cd dl_meso
......
Markdown is supported
0%
or
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment